
. 
. **Feeling Thermo Models 
. 
. encode country, gen(country_cat)

. 
. *Average (all but US) 
. 
. egen ft_avg_all = rowmean(ft_mexico ft_china ft_UK ft_germ ft_japan ft_PR)
(85 missing values generated)

. 
. 
. *Ethnocentrism FT 
. 
. egen ft_ethno = rowmean(ft_china ft_mexico ft_UK ft_germ ft_japan ft_PR)
(85 missing values generated)

. replace ft_ethno = ft_ethno/100
(20,298 real changes made)

. replace ft_ethno = 1-abs(ft_ethno)
(20,113 real changes made)

. 
. *PR FT 
. 
. gen ft_ethno_PR = ft_us - ft_PR
(256 missing values generated)

. replace ft_ethno_PR=ft_ethno_PR/100
(17,874 real changes made)

. 
. 
. *Models Reported in online appendix -- Table A7
. 
. reg profile_chose b4.country_cat##c.ft_ethno c.mark_up i.rating_cat ///
> i.pid3_lean, cluster(id)

Linear regression                               Number of obs     =     19,830
                                                F(12, 991)        =     441.13
                                                Prob > F          =     0.0000
                                                R-squared         =     0.2009
                                                Root MSE          =     .44712

                                                           (Std. Err. adjusted for 992 clusters in id)
------------------------------------------------------------------------------------------------------
                                     |               Robust
                      profile_chosen |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------------------------------+----------------------------------------------------------------
                         country_cat |
A country outside the United States  |  -.1068741    .025975    -4.11   0.000    -.1578464   -.0559018
                              China  |   -.196033   .0291963    -6.71   0.000    -.2533267   -.1387393
                            Germany  |  -.0283564   .0245781    -1.15   0.249    -.0765874    .0198747
                                     |
                            ft_ethno |   .1869963   .0345888     5.41   0.000     .1191206     .254872
                                     |
              country_cat#c.ft_ethno |
A country outside the United States  |  -.1858879   .0538818    -3.45   0.001    -.2916235   -.0801524
                              China  |  -.3105345   .0602852    -5.15   0.000    -.4288358   -.1922332
                            Germany  |  -.2558542   .0515457    -4.96   0.000    -.3570055   -.1547028
                                     |
                             mark_up |  -.3600315   .0103531   -34.78   0.000    -.3803481    -.339715
                                     |
                          rating_cat |
                   4 out of 5 stars  |   .1872143   .0091004    20.57   0.000     .1693561    .2050726
                   5 out of 5 stars  |   .3229691   .0097026    33.29   0.000     .3039291    .3420091
                                     |
                           pid3_lean |
                   Pure Independent  |  -.0054818   .0050852    -1.08   0.281    -.0154608    .0044972
                         Republican  |  -.0009808   .0033651    -0.29   0.771    -.0075843    .0056228
                                     |
                               _cons |   .5733231   .0191539    29.93   0.000     .5357362      .61091
------------------------------------------------------------------------------------------------------

. est store m1

. 
. reg profile_chose b4.country_cat##c.ft_ethno_PR c.mark_up i.rating_cat ///
> i.pid3_lean, cluster(id)

Linear regression                               Number of obs     =     19,670
                                                F(12, 983)        =     461.81
                                                Prob > F          =     0.0000
                                                R-squared         =     0.2035
                                                Root MSE          =     .44639

                                                           (Std. Err. adjusted for 984 clusters in id)
------------------------------------------------------------------------------------------------------
                                     |               Robust
                      profile_chosen |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------------------------------+----------------------------------------------------------------
                         country_cat |
A country outside the United States  |   -.157016   .0122839   -12.78   0.000    -.1811217   -.1329103
                              China  |  -.2868268     .01367   -20.98   0.000    -.3136525    -.260001
                            Germany  |  -.1055726   .0116815    -9.04   0.000    -.1284962    -.082649
                                     |
                         ft_ethno_PR |   .1500764   .0210813     7.12   0.000     .1087069    .1914458
                                     |
           country_cat#c.ft_ethno_PR |
A country outside the United States  |  -.1765613   .0339596    -5.20   0.000     -.243203   -.1099196
                              China  |  -.2608843   .0368429    -7.08   0.000    -.3331841   -.1885845
                            Germany  |  -.1893561   .0331297    -5.72   0.000    -.2543693    -.124343
                                     |
                             mark_up |   -.359989   .0104178   -34.56   0.000    -.3804327   -.3395454
                                     |
                          rating_cat |
                   4 out of 5 stars  |   .1869064   .0091149    20.51   0.000     .1690195    .2047933
                   5 out of 5 stars  |   .3233437   .0097159    33.28   0.000     .3042775    .3424099
                                     |
                           pid3_lean |
                   Pure Independent  |   -.004666    .005065    -0.92   0.357    -.0146054    .0052734
                         Republican  |   .0005933   .0035009     0.17   0.865    -.0062768    .0074634
                                     |
                               _cons |   .6280987   .0112927    55.62   0.000     .6059382    .6502592
------------------------------------------------------------------------------------------------------

. est store m2

. 
. esttab m1 m2 using TableA7.csv, ///
> se r2 nobaselevels obslast nonumber varwidth(16) nogap replace 
(output written to TableA7.csv)

. 
. 
. **MWTP
. 
. *create TableA8
. 
. file open TableA8 using TableA8.txt, write replace

. 
. file write TableA8 "Measure   " _tab "Country    " _tab    "Ethno" _tab    "   MTWP (95%CI)" _n

. 
. 
. *FT Approach 
. 
. est restore m1
(results m1 are active now)

. sum ft_ethno, d

                          ft_ethno
-------------------------------------------------------------
      Percentiles      Smallest
 1%            0              0
 5%          .13              0
10%     .2033334              0       Obs              20,378
25%     .3116667              0       Sum of Wgt.      20,378

50%     .4316667                      Mean           .4388043
                        Largest       Std. Dev.      .1943371
75%     .5483333              1
90%         .695              1       Variance       .0377669
95%     .8083333              1       Skewness       .3441326
99%     .9783334              1       Kurtosis       3.380334

. 
. *China
. nlcom (_b[2.country]+(_b[2.country#c.ft_ethno]*.205))/_b[mark_up]

       _nl_1:  (_b[2.country]+(_b[2.country#c.ft_ethno]*.205))/_b[mark_up]

------------------------------------------------------------------------------
profile_ch~n |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
       _nl_1 |   .7213051   .0576758    12.51   0.000     .6082625    .8343476
------------------------------------------------------------------------------

. file write TableA8  %9s "Avg FT    " _tab "China        " _tab   "Low  " _tab %7.2f (r(b)[1,1]) " ("  %7.2f (  r(b)[1,1] - (1.96*sqrt(r(V)[1,1]))   )  "," %7.2f (  r(b)[1,1] + (1.96*sqrt(r(V)[1,1]))   )    ")"  _n

. 
. nlcom (_b[2.country]+(_b[2.country#c.ft_ethno]*.43))/_b[mark_up]

       _nl_1:  (_b[2.country]+(_b[2.country#c.ft_ethno]*.43))/_b[mark_up]

------------------------------------------------------------------------------
profile_ch~n |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
       _nl_1 |   .9153721   .0465741    19.65   0.000     .8240885    1.006656
------------------------------------------------------------------------------

. file write TableA8  %9s "Avg FT    " _tab "China        " _tab   "Med  " _tab %7.2f (r(b)[1,1]) " ("  %7.2f (  r(b)[1,1] - (1.96*sqrt(r(V)[1,1]))   )  "," %7.2f (  r(b)[1,1] + (1.96*sqrt(r(V)[1,1]))   )    ")"  _n

. 
. nlcom (_b[2.country]+(_b[2.country#c.ft_ethno]*.7))/_b[mark_up]

       _nl_1:  (_b[2.country]+(_b[2.country#c.ft_ethno]*.7))/_b[mark_up]

------------------------------------------------------------------------------
profile_ch~n |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
       _nl_1 |   1.148253   .0683638    16.80   0.000     1.014262    1.282243
------------------------------------------------------------------------------

. file write TableA8  %9s "Avg FT    " _tab "China        " _tab   "High  " _tab %7.2f (r(b)[1,1]) " ("  %7.2f (  r(b)[1,1] - (1.96*sqrt(r(V)[1,1]))   )  "," %7.2f (  r(b)[1,1] + (1.96*sqrt(r(V)[1,1]))   )    ")"  _n

. 
. 
. 
. 
. *German  
. nlcom (_b[3.country]+(_b[3.country#c.ft_ethno]*.205))/_b[mark_up]

       _nl_1:  (_b[3.country]+(_b[3.country#c.ft_ethno]*.205))/_b[mark_up]

------------------------------------------------------------------------------
profile_ch~n |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
       _nl_1 |   .2244427   .0438871     5.11   0.000     .1384256    .3104599
------------------------------------------------------------------------------

. file write TableA8  %9s "Avg FT    " _tab "Germany      " _tab   "Low  " _tab %7.2f (r(b)[1,1]) " ("  %7.2f (  r(b)[1,1] - (1.96*sqrt(r(V)[1,1]))   )  "," %7.2f (  r(b)[1,1] + (1.96*sqrt(r(V)[1,1]))   )    ")"  _n

. 
. nlcom (_b[3.country]+(_b[3.country#c.ft_ethno]*.43))/_b[mark_up]

       _nl_1:  (_b[3.country]+(_b[3.country#c.ft_ethno]*.43))/_b[mark_up]

------------------------------------------------------------------------------
profile_ch~n |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
       _nl_1 |   .3843376   .0311972    12.32   0.000     .3231923    .4454829
------------------------------------------------------------------------------

. file write TableA8  %9s "Avg FT    " _tab "Germany      " _tab   "Med  " _tab %7.2f (r(b)[1,1]) " ("  %7.2f (  r(b)[1,1] - (1.96*sqrt(r(V)[1,1]))   )  "," %7.2f (  r(b)[1,1] + (1.96*sqrt(r(V)[1,1]))   )    ")"  _n

. 
. nlcom (_b[3.country]+(_b[3.country#c.ft_ethno]*.7))/_b[mark_up]

       _nl_1:  (_b[3.country]+(_b[3.country#c.ft_ethno]*.7))/_b[mark_up]

------------------------------------------------------------------------------
profile_ch~n |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
       _nl_1 |   .5762114   .0516132    11.16   0.000     .4750513    .6773715
------------------------------------------------------------------------------

. file write TableA8  %9s "Avg FT    " _tab "Germany      " _tab   "High  " _tab %7.2f (r(b)[1,1]) " ("  %7.2f (  r(b)[1,1] - (1.96*sqrt(r(V)[1,1]))   )  "," %7.2f (  r(b)[1,1] + (1.96*sqrt(r(V)[1,1]))   )    ")"  _n

. 
. 
. 
. *Other Country 
. 
. nlcom (_b[1.country]+(_b[1.country#c.ft_ethno]*.205))/_b[mark_up]

       _nl_1:  (_b[1.country]+(_b[1.country#c.ft_ethno]*.205))/_b[mark_up]

------------------------------------------------------------------------------
profile_ch~n |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
       _nl_1 |   .4026901   .0476043     8.46   0.000     .3093874    .4959928
------------------------------------------------------------------------------

. file write TableA8  %9s "Avg FT    " _tab "Outside U.S." _tab   "Low  " _tab %7.2f (r(b)[1,1]) " ("  %7.2f (  r(b)[1,1] - (1.96*sqrt(r(V)[1,1]))   )  "," %7.2f (  r(b)[1,1] + (1.96*sqrt(r(V)[1,1]))   )    ")"  _n

. 
. nlcom (_b[1.country]+(_b[1.country#c.ft_ethno]*.43))/_b[mark_up]

       _nl_1:  (_b[1.country]+(_b[1.country#c.ft_ethno]*.43))/_b[mark_up]

------------------------------------------------------------------------------
profile_ch~n |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
       _nl_1 |   .5188599   .0341876    15.18   0.000     .4518535    .5858663
------------------------------------------------------------------------------

. file write TableA8  %9s "Avg FT    " _tab "Outside U.S." _tab   "Med  " _tab %7.2f (r(b)[1,1]) " ("  %7.2f (  r(b)[1,1] - (1.96*sqrt(r(V)[1,1]))   )  "," %7.2f (  r(b)[1,1] + (1.96*sqrt(r(V)[1,1]))   )    ")"  _n

. 
. nlcom (_b[1.country]+(_b[1.country#c.ft_ethno]*.7))/_b[mark_up]

       _nl_1:  (_b[1.country]+(_b[1.country#c.ft_ethno]*.7))/_b[mark_up]

------------------------------------------------------------------------------
profile_ch~n |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
       _nl_1 |   .6582636   .0539221    12.21   0.000     .5525783     .763949
------------------------------------------------------------------------------

. file write TableA8  %9s "Avg FT    " _tab "Outside U.S." _tab   "High  " _tab %7.2f (r(b)[1,1]) " ("  %7.2f (  r(b)[1,1] - (1.96*sqrt(r(V)[1,1]))   )  "," %7.2f (  r(b)[1,1] + (1.96*sqrt(r(V)[1,1]))   )    ")"  _n

. 
. 
. 
. *FT - PR Approach 
. est restore m2
(results m2 are active now)

. sum ft_ethno_PR,d

                         ft_ethno_PR
-------------------------------------------------------------
      Percentiles      Smallest
 1%         -.53             -1
 5%         -.25           -.99
10%         -.12           -.86       Obs              20,207
25%            0           -.86       Sum of Wgt.      20,207

50%          .14                      Mean           .1853516
                        Largest       Std. Dev.      .2963369
75%          .36              1
90%          .57              1       Variance       .0878156
95%          .77              1       Skewness       .2275651
99%          .95              1       Kurtosis       3.561071

. 
. 
. *China
. nlcom (_b[2.country]+(_b[2.country#c.ft_ethno_PR]*-.11))/_b[mark_up]

       _nl_1:  (_b[2.country]+(_b[2.country#c.ft_ethno_PR]*-.11))/_b[mark_up]

------------------------------------------------------------------------------
profile_ch~n |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
       _nl_1 |   .7170482   .0521855    13.74   0.000     .6147666    .8193298
------------------------------------------------------------------------------

. file write TableA8  %9s "US-PR FT" _tab "China        " _tab   "Low  " _tab %7.2f (r(b)[1,1]) " ("  %7.2f (  r(b)[1,1] - (1.96*sqrt(r(V)[1,1]))   )  "," %7.2f (  r(b)[1,1] + (1.96*sqrt(r(V)[1,1]))   )    ")"  _n

. 
. nlcom (_b[2.country]+(_b[2.country#c.ft_ethno_PR]*.14))/_b[mark_up]

       _nl_1:  (_b[2.country]+(_b[2.country#c.ft_ethno_PR]*.14))/_b[mark_up]

------------------------------------------------------------------------------
profile_ch~n |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
       _nl_1 |   .8982234   .0461909    19.45   0.000     .8076908    .9887559
------------------------------------------------------------------------------

. file write TableA8  %9s "US-PR FT" _tab "China        " _tab   "Med  " _tab %7.2f (r(b)[1,1]) " ("  %7.2f (  r(b)[1,1] - (1.96*sqrt(r(V)[1,1]))   )  "," %7.2f (  r(b)[1,1] + (1.96*sqrt(r(V)[1,1]))   )    ")"  _n

. 
. 
. nlcom (_b[2.country]+(_b[2.country#c.ft_ethno_PR]*.58))/_b[mark_up]

       _nl_1:  (_b[2.country]+(_b[2.country#c.ft_ethno_PR]*.58))/_b[mark_up]

------------------------------------------------------------------------------
profile_ch~n |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
       _nl_1 |   1.217092   .0669964    18.17   0.000     1.085781    1.348402
------------------------------------------------------------------------------

. file write TableA8  %9s "US-PR FT" _tab "China        " _tab   "High  " _tab %7.2f (r(b)[1,1]) " ("  %7.2f (  r(b)[1,1] - (1.96*sqrt(r(V)[1,1]))   )  "," %7.2f (  r(b)[1,1] + (1.96*sqrt(r(V)[1,1]))   )    ")"  _n

. 
. 
. *Germany 
. nlcom (_b[3.country]+(_b[3.country#c.ft_ethno_PR]*-.11))/_b[mark_up]

       _nl_1:  (_b[3.country]+(_b[3.country#c.ft_ethno_PR]*-.11))/_b[mark_up]

------------------------------------------------------------------------------
profile_ch~n |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
       _nl_1 |   .2354056   .0394808     5.96   0.000     .1580247    .3127866
------------------------------------------------------------------------------

. file write TableA8  %9s "US-PR FT" _tab "Germany      " _tab   "Low  " _tab %7.2f (r(b)[1,1]) " ("  %7.2f (  r(b)[1,1] - (1.96*sqrt(r(V)[1,1]))   )  "," %7.2f (  r(b)[1,1] + (1.96*sqrt(r(V)[1,1]))   )    ")"  _n

. 
. nlcom (_b[3.country]+(_b[3.country#c.ft_ethno_PR]*.14))/_b[mark_up]

       _nl_1:  (_b[3.country]+(_b[3.country#c.ft_ethno_PR]*.14))/_b[mark_up]

------------------------------------------------------------------------------
profile_ch~n |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
       _nl_1 |    .366907   .0311465    11.78   0.000     .3058609     .427953
------------------------------------------------------------------------------

. file write TableA8  %9s "US-PR FT" _tab "Germany      " _tab   "Med  " _tab %7.2f (r(b)[1,1]) " ("  %7.2f (  r(b)[1,1] - (1.96*sqrt(r(V)[1,1]))   )  "," %7.2f (  r(b)[1,1] + (1.96*sqrt(r(V)[1,1]))   )    ")"  _n

. 
. 
. nlcom (_b[3.country]+(_b[3.country#c.ft_ethno_PR]*.58))/_b[mark_up]

       _nl_1:  (_b[3.country]+(_b[3.country#c.ft_ethno_PR]*.58))/_b[mark_up]

------------------------------------------------------------------------------
profile_ch~n |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
       _nl_1 |   .5983493    .050775    11.78   0.000     .4988321    .6978664
------------------------------------------------------------------------------

. file write TableA8  %9s "US-PR FT" _tab "Germany      " _tab   "High  " _tab %7.2f (r(b)[1,1]) " ("  %7.2f (  r(b)[1,1] - (1.96*sqrt(r(V)[1,1]))   )  "," %7.2f (  r(b)[1,1] + (1.96*sqrt(r(V)[1,1]))   )    ")"  _n

. 
. 
. 
. *Other Country 
. nlcom (_b[1.country]+(_b[1.country#c.ft_ethno_PR]*-.11))/_b[mark_up]

       _nl_1:  (_b[1.country]+(_b[1.country#c.ft_ethno_PR]*-.11))/_b[mark_up]

------------------------------------------------------------------------------
profile_ch~n |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
       _nl_1 |   .3822179   .0427052     8.95   0.000     .2985173    .4659185
------------------------------------------------------------------------------

. file write TableA8  %9s "US-PR FT" _tab "Outside U.S." _tab   "Low  " _tab %7.2f (r(b)[1,1]) " ("  %7.2f (  r(b)[1,1] - (1.96*sqrt(r(V)[1,1]))   )  "," %7.2f (  r(b)[1,1] + (1.96*sqrt(r(V)[1,1]))   )    ")"  _n

. 
. nlcom (_b[1.country]+(_b[1.country#c.ft_ethno_PR]*.14))/_b[mark_up]

       _nl_1:  (_b[1.country]+(_b[1.country#c.ft_ethno_PR]*.14))/_b[mark_up]

------------------------------------------------------------------------------
profile_ch~n |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
       _nl_1 |   .5048337     .03416    14.78   0.000     .4378813    .5717861
------------------------------------------------------------------------------

. file write TableA8  %9s "US-PR FT" _tab "Outside U.S." _tab   "Med  " _tab %7.2f (r(b)[1,1]) " ("  %7.2f (  r(b)[1,1] - (1.96*sqrt(r(V)[1,1]))   )  "," %7.2f (  r(b)[1,1] + (1.96*sqrt(r(V)[1,1]))   )    ")"  _n

. 
. 
. nlcom (_b[1.country]+(_b[1.country#c.ft_ethno_PR]*.58))/_b[mark_up]

       _nl_1:  (_b[1.country]+(_b[1.country#c.ft_ethno_PR]*.58))/_b[mark_up]

------------------------------------------------------------------------------
profile_ch~n |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
       _nl_1 |   .7206374   .0530766    13.58   0.000     .6166093    .8246655
------------------------------------------------------------------------------

. file write TableA8  %9s "US-PR FT" _tab "Outside U.S." _tab   "High  " _tab %7.2f (r(b)[1,1]) " ("  %7.2f (  r(b)[1,1] - (1.96*sqrt(r(V)[1,1]))   )  "," %7.2f (  r(b)[1,1] + (1.96*sqrt(r(V)[1,1]))   )    ")"  _n

. 
. 
. 
. file close TableA8
